Elevated UV-B radiation reduces genome stability in plants

Long-term depletion of the stratospheric ozone layer contributes to an increase in terrestrial solar ultraviolet-B radiation. This has deleterious effects on living organisms, such as DNA damage. When exposed to elevated ultraviolet-B radiation (UV-B; 280-315 nm), plants display a wide variety of physiological and morphological responses characterized as acclimation and adaptation. Here we show, using special sun simulators, that elevated solar UV-B doses increase the frequency of somatic homologous DNA rearrangements in Arabidopsis and tobacco plants. Increases in recombination are accompanied by a strong induction of photolyase and Rad51 gene expression. These genes are putatively involved in major DNA repair pathways, photoreactivation and recombination repair. In mutant Arabidopsis plants that are deficient in photoreactivating ultraviolet-induced cyclobutane pyrimidine dimers, recombination under elevated UV-B regimes greatly exceeds wild-type levels. Our results show that homologous recombination repair pathways might be involved in eliminating UV-B-induced DNA lesions in plants. Thus, increases in terrestrial solar UV-B radiation as forecasted for the early 21st century may affect genome stability in plants.     

量子全加法器的修改和算法研究

通过与经典全加器的基本模型进行比较后,讨论了一个改进后的量子平面加法器的基本构型.对其原理、组件和算法进行了研究,比较了本加法器两个主要组件与一般量子加法器的不同.作为应用的例,设计了一个n比特量子全加法器的模型,对其具体运算过程和基本功能进行了说明.     

A multiple intelligent agent system for credit risk prediction via an optimization of localized generalization error with diversity

Company bankruptcies cost billions of dollars in losses to banks each year. Thus credit risk prediction is a critical part of a bank＇s loan approval decision process. Traditional financial models for credit risk prediction are no longer adequate for describing today＇s complex relationship between the financial health and potential bankruptcy of a company. In this work, a multiple classifier system （embedded in a multiple intelligent agent system） is proposed to predict the financial health of a company. In our model, each individual agent （classifier） makes a prediction on the likelihood of credit risk based on only partial information of the company. Each of the agents is an expert, but has limited knowledge （represented by features） about the company. The decisions of all agents are combined together to form a final credit risk prediction. Experiments show that our model out-performs other existing methods using the benchmarking Compustat American Corporations dataset.     

Impedance Studies on Starch-NH_4NO_3 Films

1 Results Starch is considered a suitable source material because of its inherent biodegradability,ready viability and relatively low cost[1].In the present work,polymer electrolytes based on starch have been prepared by the solution cast technique.The conductivity of the films is characterized using impedance spectroscopy at room temperatures.The imaginary impedance (Zi) versus real impedance (ZR) plot of pure starch films consists of a semicircle.The bulk resistance (Rb) was taken from the intercept o...